Triple
T38160286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palatino Arabic |
E952996
|
entity |
| Predicate | languageSystem |
P203771
|
FINISHED |
| Object | Arabic layout engine |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Arabic layout engine | Statement: [Palatino Arabic, languageSystem, Arabic layout engine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageSystem Context triple: [Palatino Arabic, languageSystem, Arabic layout engine]
-
A.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
B.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
D.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
-
E.
languageFamilyUsedFor
Indicates that a particular language family is employed or utilized for a specific purpose, context, or function.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76f0b93c48190a117319ab3a9f282 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a01ed1790148190b08c1dba53de4371 |
completed | May 11, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_6a01e9c20798819085760b377dc7b3fa |
completed | May 11, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_6a01ed16dfe88190a030c75107b954a5 |
completed | May 11, 2026, 2:52 p.m. |
Created at: May 3, 2026, 4:21 p.m.